Cyclic shift delay detection using autocorrelations

ABSTRACT

Systems, apparatus and methods for determining a cyclic shift diversity (CSD) mode are presented. Examples use two different autocorrelations to determine a current CSD mode. Specifically, a delay-based autocorrelation and a cyclic shift-based autocorrelation are each computed then compared to each other, for example, by taking a difference of the two autocorrelations. A multipath signal leads to similar autocorrelations, where as a signal with a CSD mode enabled leads to dissimilar autocorrelations. By examining the number of peaks in the delay-based autocorrelation or the autocorrelation difference, a current CSD mode may be determined.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to U.S. patent application Ser. No.13/624,653, entitled “Cyclic shift delay detection using signaling” andfiled on Sep. 21, 2012, the contents of which are incorporated herein byreference.

This application is related to U.S. patent application Ser. No.13/624,646, entitled “Cyclic shift delay detection using a channelimpulse response” and filed on Sep. 21, 2012, the contents of which areincorporated herein by reference.

BACKGROUND

I. Field of the Invention

This disclosure relates generally to apparatus and methods for mobilepositioning, and more particularly to determining final transmission ina cyclic-shift diversity (CSD) signaling mode.

II. Background

To estimate a location, a mobile device may capture received signalstrength indication (RSSI) measurements from three or more accesspoints. A server or the mobile device itself may apply trilateration tothese RSSI measurements to estimate a position of the mobile device,however, these RSSI measurements have a large standard deviation.Unfortunately, trilateration with such RSSI measurements results in ahigh level of uncertainty because of the uncertainty of the RSSImeasurement levels.

To alleviate high uncertainties associated with RSSI measurements,round-trip time (RTT) measurements may be used. RTT measurementsadvantageously have a much lower level of uncertainty than the RSSImeasurements. RTT measurements record a round-trip time from initiatinga signal from the mobile device to an access point and back to themobile device. Though several uncertainties exist with RTT measurement,these variables may be determined or estimated with less uncertaintythat is associated with RSSI measurements. A server or a mobile devicemay use the RTT measurements in trilateration to more accuratelyestimate the position of the mobile device.

Recently, Cyclic Shift Diversity (CSD) has been introduced into the IEEE802.11n standard to improve reception by spatial spreading the streamsacross multiple antennas and transmitting the same signal with differentcyclic shifts. With the effects of multiple transmissions and multipath,RTT measurements no longer provide reliable time measurements because ofmultiple possible start times.

Various CSD modes are defined in the IEEE 802.11n standard. Asingle-transmitter system does not use cyclic shifting (CSD mode 1). Inother words, CSD is disabled when operating in CSD mode 1 and only onetransmitter is operating. When two or more transmitters are operating,cyclic shifting may be disabled and identical signals are transmittedfrom each antenna. Alternatively, cyclic shifting may be enabled and adifferent time-shifted signal of an original signal is transmitted fromeach antenna. In CSD mode 2, two transmitters transmit: a firsttransmitter transmits the original signal and a second transmittertransmits a time-shifted signal advanced by 200 ns using cyclicshifting. In CSD mode 3, three transmitters transmit: a firsttransmitter transmits the original signal, a second transmittertransmits a time-shifted signal advanced by 100 ns, and a thirdtransmitter transmits a signal advanced by an additional 100 ns. In CSDMode 4, four transmitters transmit: a first transmitter transmits theoriginal signal, a second transmitter advances the signal by 50 ns, athird transmitter advances the signal by an additional 50 ns, and afourth transmitter advances the signal by another 50 ns for a total of150 ns from the original signal. More CSD modes may be defined in thefuture. These CSD modes are recommendations and not requirements. Aspecific manufacturer is free to utilized non-standard implementations.As such, a non-standard CSD mode may be defined base on a number oftransmitters (e.g., 2, 3 or 4 transmitters) along with a temporalspacing (e.g., 50 ns, 100 ns, 150 ns, 200 ns).

As a result, RTT measurements may be skewed with false positive signalswhen CSD is enabled. Alternatively, multipath may appear as amulti-transmitter CSD mode signal when in fact CSD is disabled and onlya signal transmitter is used. Without some other detection andcorrection processing, RTT measurements may select a first-to-arrivesignal (having a transmitter advanced signal using cyclic shifting froma second or subsequent transmitter) rather than the last transmission(from the first transmitter).

Therefore, what is needed is a way to determine if CSD is enabled. Also,if enabled, what CSD mode is operational, thereby providing accurate RTTmeasurement that may be used for mobile device positioning.

BRIEF SUMMARY

Disclosed are systems, apparatus and methods for communicating anddetermining a CSD mode.

According to some aspects, disclosed is a method for finding cyclicshift diversity (CSD) using autocorrelations, the method comprising:receiving an orthogonal frequency-division multiplexing (OFDM) signal;computing a delay-based autocorrelation of the OFDM signal to form adelay-based autocorrelation result; computing a cyclic shift-basedautocorrelation of the OFDM signal to form a cyclic shift-basedautocorrelation result; comparing the delay-based autocorrelation resultto the cyclic shift-based autocorrelation result to form a comparison;and determining a CSD mode based on the comparison.

According to some aspects, disclosed is a mobile device for findingcyclic shift diversity (CSD) using autocorrelations, the devicecomprising: a transceiver, the transceiver for receiving an orthogonalfrequency-division multiplexing (OFDM) signal; and a processor coupledto the transceiver, the processor for: computing a delay-basedautocorrelation of the OFDM signal to form a delay-based autocorrelationresult; computing a cyclic shift-based autocorrelation of the OFDMsignal to form a cyclic shift-based autocorrelation result; comparingthe delay-based autocorrelation result to the cyclic shift-basedautocorrelation result to form a comparison; and determining a CSD modebased on the comparison.

According to some aspects, disclosed is a mobile device for findingcyclic shift diversity (CSD) using autocorrelations, the devicecomprising: means for receiving an orthogonal frequency-divisionmultiplexing (OFDM) signal; means for computing a delay-basedautocorrelation of the OFDM signal to form a delay-based autocorrelationresult; means for computing a cyclic shift-based autocorrelation of theOFDM signal to form a cyclic shift-based autocorrelation result; meansfor comparing the delay-based autocorrelation result to the cyclicshift-based autocorrelation result to form a comparison; and means fordetermining a CSD mode based on the comparison.

According to some aspects, disclosed is a non-volatile computer-readablestorage medium including program code stored thereon, comprising programcode for: receiving an orthogonal frequency-division multiplexing (OFDM)signal; computing a delay-based autocorrelation of the OFDM signal toform a delay-based autocorrelation result; computing a cyclicshift-based autocorrelation of the OFDM signal to form a cyclicshift-based autocorrelation result; comparing the delay-basedautocorrelation result to the cyclic shift-based autocorrelation resultto form a comparison; and determining a CSD mode based on thecomparison.

It is understood that other aspects will become readily apparent tothose skilled in the art from the following detailed description,wherein it is shown and described various aspects by way ofillustration. The drawings and detailed description are to be regardedas illustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWING

Embodiments of the invention will be described, by way of example only,with reference to the drawings.

FIG. 1 illustrates trilateration using RSSI measurements.

FIG. 2 illustrates trilateration using RTT measurements.

FIG. 3 shows delays associated with RTT measurements.

FIGS. 4 and 5 compare relative uncertainties of RSSI and RTTmeasurements.

FIGS. 6 to 11 show various standard and non-standard implementations ofCSD modes.

FIGS. 12 to 18 show the structure for transmission of OFDM symbols withand without cyclic shifting.

FIGS. 19 to 22 illustrate effects of multipath.

FIGS. 23 to 26 illustrate effects of cyclic shift diversity.

FIGS. 27 to 34 define a first method to determine a CSD mode bysignaling CSD information between an access point and a mobile device,in accordance with some embodiments of the present invention.

FIGS. 35 to 54 show how to determine a CSD mode by using a combinationof delay-based autocorrelation and cyclic shift-based autocorrelation,in accordance with some embodiments of the present invention.

FIGS. 55 to 60 illustrate another method to determine a CSD mode byusing a channel impulse response calculation, in accordance with someembodiments of the present invention.

DETAILED DESCRIPTION

The detailed description set forth below in connection with the appendeddrawings is intended as a description of various aspects of the presentdisclosure and is not intended to represent the only aspects in whichthe present disclosure may be practiced. Each aspect described in thisdisclosure is provided merely as an example or illustration of thepresent disclosure, and should not necessarily be construed as preferredor advantageous over other aspects. The detailed description includesspecific details for the purpose of providing a thorough understandingof the present disclosure. However, it will be apparent to those skilledin the art that the present disclosure may be practiced without thesespecific details. In some instances, well-known structures and devicesare shown in block diagram form in order to avoid obscuring the conceptsof the present disclosure. Acronyms and other descriptive terminologymay be used merely for convenience and clarity and are not intended tolimit the scope of the disclosure.

Position determination techniques described herein may be implemented inconjunction with various wireless communication networks such as awireless wide area network (WWAN), a wireless local area network (WLAN),a wireless personal area network (WPAN), and so on. The term “network”and “system” are often used interchangeably. A WWAN may be a CodeDivision Multiple Access (CDMA) network, a Time Division Multiple Access(TDMA) network, a Frequency Division Multiple Access (FDMA) network, anOrthogonal Frequency Division Multiple Access (OFDMA) network, aSingle-Carrier Frequency Division Multiple Access (SC-FDMA) network,Long Term Evolution (LTE), and so on. A CDMA network may implement oneor more radio access technologies (RATs) such as cdma2000, Wideband-CDMA(W-CDMA), and so on. Cdma2000 includes IS-95, IS-2000, and IS-856standards. A TDMA network may implement Global System for MobileCommunications (GSM), Digital Advanced Mobile Phone System (D-AMPS), orsome other RAT. GSM and W-CDMA are described in documents from aconsortium named “3rd Generation Partnership Project” (3GPP). Cdma2000is described in documents from a consortium named “3rd GenerationPartnership Project 2” (3GPP2). 3GPP and 3GPP2 documents are publiclyavailable. A WLAN may be an IEEE 802.11x network, and a WPAN may be aBluetooth network, an IEEE 802.15x, or some other type of network. Thetechniques may also be implemented in conjunction with any combinationof WWAN, WLAN and/or WPAN.

A satellite positioning system (SPS) typically includes a system oftransmitters positioned to enable entities to determine their locationon or above the Earth based, at least in part, on signals received fromthe transmitters. Such a transmitter typically transmits a signal markedwith a repeating pseudo-random noise (PN) code of a set number of chipsand may be located on ground based control stations, user equipmentand/or space vehicles. In a particular example, such transmitters may belocated on Earth orbiting satellite vehicles (SVs). For example, a SV ina constellation of Global Navigation Satellite System (GNSS) such asGlobal Positioning System (GPS), Galileo, GLONASS or Compass maytransmit a signal marked with a PN code that is distinguishable from PNcodes transmitted by other SVs in the constellation (e.g., usingdifferent PN codes for each satellite as in GPS or using the same codeon different frequencies as in GLONASS). In accordance with certainaspects, the techniques presented herein are not restricted to globalsystems (e.g., GNSS) for SPS. For example, the techniques providedherein may be applied to or otherwise enabled for use in variousregional systems, such as, e.g., Quasi-Zenith Satellite System (QZSS)over Japan, Indian Regional Navigational Satellite System (IRNSS) overIndia, Beidou over China, etc., and/or various augmentation systems(e.g., an Satellite Based Augmentation System (SBAS)) that may beassociated with or otherwise enabled for use with one or more globaland/or regional navigation satellite systems. By way of example but notlimitation, an SBAS may include an augmentation system(s) that providesintegrity information, differential corrections, etc., such as, e.g.,Wide Area Augmentation System (WAAS), European Geostationary NavigationOverlay Service (EGNOS), Multi-functional Satellite Augmentation System(MSAS), GPS Aided Geo Augmented Navigation or GPS and Geo AugmentedNavigation system (GAGAN), and/or the like. Thus, as used herein an SPSmay include any combination of one or more global and/or regionalnavigation satellite systems and/or augmentation systems, and SPSsignals may include SPS, SPS-like, and/or other signals associated withsuch one or more SPS.

As used herein, a mobile device, sometimes referred to as a mobilestation (MS) or user equipment (UE), such as a cellular phone, mobilephone or other wireless communication device, personal communicationsystem (PCS) device, personal navigation device (PND), PersonalInformation Manager (PIM), Personal Digital Assistant (PDA), laptop orother suitable mobile device which is capable of receiving wirelesscommunication and/or navigation signals. The term “mobile station” isalso intended to include devices which communicate with a personalnavigation device (PND), such as by short-range wireless, infrared,wireline connection, or other connection—regardless of whether satellitesignal reception, assistance data reception, and/or position-relatedprocessing occurs at the device or at the PND. Also, “mobile station” isintended to include all devices, including wireless communicationdevices, computers, laptops, etc. which are capable of communicationwith a server, such as via the Internet, WiFi, or other network, andregardless of whether satellite signal reception, assistance datareception, and/or position-related processing occurs at the device, at aserver, or at another device associated with the network. Any operablecombination of the above are also considered a “mobile device.”

FIG. 1 illustrates trilateration using RSSI measurements. A mobiledevice (e.g., mobile station, user equipment or MS 200) receives signalsfrom multiple access points 100 (e.g., AP₁ 100-1, AP₂ 100-2 & AP₃100-3). MS 200 records RSSI measurements (e.g., RSSI₁, RSSI₂ & RSSI₃)from each access point. Knowing the location of each access point, MS200 weights their locations by the RSSI measurements to form a positionestimate.

FIG. 2 illustrates trilateration using RTT measurements. MS 200 sendssignals to multiple access points 100 (e.g., AP₁ 100-1, AP₂ 100-2 & AP₃100-3). Each access point 100 immediately sends back an acknowledgementto form a round-trip signal. The travel time of the round-trip signalmay be determined for each access point as RTT₁, RTT₂ and RTT₃,respectfully. With knowledge of the location of each access point 100and the respective RTT, MS 200 may calculate its position estimate.

FIG. 3 shows delays associated with RTT measurements. The total delay isreferred to as a turn-around calibration factor or TCF 300. The TCF 300may be approximated, assumed, measured or estimated. At 302, a firstdelay is the MS transmitter delay (t_(MSTX)). At 304, a second delay isthe uplink path propagation delay (t_(UP)), which is indicative ofrange. At 306, a third delay represents receiver delays in the accesspoint (t_(APRX)). At 308, a fourth delay is the processor delay in theaccess point (t_(APPR)). At 310, a fifth delay is the transmitter delayin the access point (t_(APTX)). At 312, a sixth delay is the downlinkpath propagation delays (t_(DOWN)), which is also indicative of range.At 314, a seventh delay is the receiver delay in MS 200 (t_(MSRX)).

Both delays indicative of range (namely, t_(UP) and t_(DOWN)) may beexcluded from TCF 300. Therefore, the measured delay may be adjusted byTCF 300 to result in the signal travel time. That is, RTTmeasured−TCF=RTT. Finally, RTT may be converted to a range by computingthe one-way time and adjusting for the speed of light (range=c*{RTT/2},where c represents the speed of light and {RTT/2} represents the one-waytime of signal travel).

FIGS. 4 and 5 compare relative uncertainties of RSSI and RTTmeasurements. In FIG. 4, a probability density function (PDF) is shownfor RSSI measurements converted from power [dBm] to range [m]. The PDFis represented by a standard deviation (σ_(RSSI)) or variance (σ²_(RSSI)) of the RSSI measurements. In FIG. 5, a PDF is shown for RTTmeasurements converted from time [s] to range [m]. The RTT measurementsare represented by a standard deviation (σ_(RTT)) or variance (σ²_(RTT)) of the RTT measurements. As shown, the range estimateuncertainty of the RSSI variance is much larger than that of the RTTvariance. Therefore, if RTT measurements are available, RTT may providea position estimate with more accuracy (or less uncertainty) than theRSSI measurements. In equation form, the variances are compared with (σ²_(RSSI)>>σ_(RTT)).

FIGS. 6 to 11 show various standard and non-standard implementations ofCSD modes. In FIG. 6 tabulates recommended CSD modes. A first mode (CSDmode 1) disables CSD and uses only one transmitter. The remaining modesenable CSD. A second mode (CSD mode 2) uses two transmitters space apartby 200 nanoseconds (ns). The first transmitter transmits the originalsignal with no temporal shift. The second transmitter advances theoriginal signal by the 200 ns and wraps the final 200 ns as the first200 ns. A third mode (CSD mode 3) uses three transmitters eachtemporally spaced apart by 100 ns. The first transmitter transmits theoriginal signal with 0 ns of cyclic shift. The second transmittertransmits the original signal with a 100 ns cyclic shift. The thirdtransmitter transmits the original signal with a 200 ns cyclic shift. Afourth mode (CSD mode 4) uses four transmitters each temporally spacedapart by 50 ns. The first transmitter transmits the original signal with0 ns of cyclic shift. The second transmitter transmits the originalsignal with a 50 ns cyclic shift. The third transmitter transmits theoriginal signal with a 100 ns cyclic shift. The fourth transmittertransmits the original signal with a 150 ns cyclic shift. Additionalmodes may be defined in the future. In addition, an access point ormobile phone manufacturer may customize a CSD mode by defining a numberof transmitters and a temporal spacing between transmitters.

In FIG. 7, an autocorrelation R₁(τ) of a received signal transmittedusing CSD mode 1 is shown. The autocorrelation includes a single peakcentered about τ=0. In FIG. 8, an autocorrelation R_(A)(τ) of a receivedsignal transmitted using CSD mode 2 is shown. The autocorrelationincludes two peaks centered about τ=0 and τ=−200 ns. In FIG. 9, anautocorrelation R₃(τ) of a received signal transmitted using CSD mode 3is shown. The autocorrelation includes three peaks centered about τ=0,τ=−100 and τ=−200 ns. In FIG. 10, an autocorrelation R₄(τ) of a receivedsignal transmitted using CSD mode 4 is shown. The autocorrelationincludes four peaks centered about τ=0, τ=−50, τ=−100 and τ=−150 ns. InFIG. 11, an autocorrelation R₅(τ) of a non-standard received signaltransmitted using CSD mode 5 is shown. The autocorrelation includes npeaks spaced by X ns.

FIGS. 12 to 18 show the structure for transmission of OFDM symbols withand without cyclic shifting. In FIG. 12, a transmitted OFDM signal isshown. The OFDM signal includes a preamble (N_(PRE)=16 μs) and a signalfield (N_(SF)=4 μs), followed by a payload comprising OFDM symbols(N_(PAYLOAD)=20 μs, 28 μs or 32 μs for a variable number of OFDM symbolsN_(SYM)=5, 7 or 8, respectively). Five OFDM symbols are represented by112 bits or 14 bytes. Seven OFDM symbols are represented by 160 bits or20 bytes. Eight OFDM symbols are represented by 192 bits or 24 bytes.One OFDM symbol is N=4 μs long.

In FIG. 13, a structure of OFDM symbols is shown. A variable number ofOFDM symbols are created from a variable number of 8-bit bytes. In theexample shown, 14 8-bit bytes or 112 bits need to be transmitted at 6Mbps. To determine the number of OFDM symbols required, the division of112 bits by 6 Mbps is rounded up to an integer number of symbols from4.667 symbols to 5 OFDM symbols. Each OFDM symbol (of duration N=4 μs or160 samples) includes a guard interval (GI) of 1 section long along withthe information (N_(g)=0.8 μs or 32 samples from start to end)comprising for 4 sections totaling 5 sections. The GI (N−N_(g)=3.2 μs or128 samples) is created from copying the end second of the information.Also shown is a forward cyclic shifted OFDM symbol. The cyclic shiftedOFDM symbol is shown shifted by 200 ns for a CSD mode 2. Therefore, afirst transmitter transmits the OFDM symbol and a second transmittertransmits the cyclic shifted OFDM symbol.

FIGS. 14-18 show the process of creating a guard interval (GI) and acyclic shift delay (CSD) in more detail. In FIG. 14, an OFDM symbol isshown of duration N=4 μs. The OFDM symbol includes a GI and information.In FIG. 15, a process to create the GI is shown by copying the end ofthe information as the GI. The GI is one of two lengths (N_(g)=0.4 μs or0.8 μs). The information is N_(S)=3.2 μs long. In FIG. 16, a firstcyclic shifted symbol shifted by 200 ns (CSD mode 2), 100 ns (CSD mode3) or 50 ns (CSD mode 4) may be imposed on the previous figure.

In FIG. 17, two successive OFDM symbols (k and k+1) for a firsttransmitter are shown. In FIG. 18, two successive OFDM symbols (k andk+1) having a cyclic shift of 200 ns for a second transmitter are shown.

FIGS. 19 to 22 illustrate effects of multipath. In FIG. 19, an accesspoint (AP₁ 100) transmits a single signal. The signal follows a directpath (Path A) and an indirect path (Path B) to a receiver at MS 200. Thesignal following the indirect path causes a delay of Δ when compared tothe direct path signal. In FIG. 20, the transmission of three sequentialsymbols is shown. A first symbol k−1 is followed by a second symbol k,which is followed by a third symbol k+1 at times t_(k−1), t_(k) andt_(k+1), respectfully. In FIG. 21, the three symbols are received alongtwo paths: the direct path (Path A) and the indirect path (Path B).Along the direct path, symbol k is received at t_(k)+D, where t_(k) isthe time symbol k was transmitted and D is the travel time. Along theindirect path, symbol k is received at t_(k)+Δ+D, where A is the timedifference between the indirect path and the direct path. In FIG. 22, anautocorrelation R(τ) of the received signal of FIG. 21 is shown. A pairof correlation peaks spaced apart by Δ occurs for each OFDM symbol. Aswill be explained below, the pair of correlation peaks may beinterpreted as a CSD mode 1 signal.

FIGS. 23 to 26 illustrate effects of cyclic shift diversity. In FIG. 23,two direct paths are shown. The AP₁ includes a first transmitter Tx₁transmitting a first signal to MS 200 along a first path (Path 1) and asecond transmitter Tx₂ transmitting a second signal to MS 200 along asecond path (Path 2). The time delay Δ between the two paths is assumedto be zero. In this case, the first signal is an original signal and thesecond signal is a cyclic shifted signal. In FIG. 24, three symbols ofthe two signals are shown. The first signal includes three symbols(symbol k−1, symbol k and symbol k+1) from the first transmitter Tx₁ andthe second signal includes cyclic shifted versions of the same symbols(CS symbol k−1, CS symbol k and CS symbol k+1) but cyclic shifted by−200 ns from the second transmitter Tx₂. The three symbols aretransmitted at t_(k−1), t_(k) and t_(k+1). In FIG. 25, the two signalsare received as an overlapping signal. Because Δ is assumed to be zero,each symbol and cyclic shifted version of the symbol are received at thesame time t_(k)+D, where t_(k) represents the transmit time and Drepresents the delay of travel time.

In FIG. 26, an autocorrelation R(τ) of the received signal of FIG. 25 isshown. A pair of correlation peaks spaced apart by 200 ns occurs foreach OFDM symbol. The pair of correlation peaks may be interpreted as aCSD mode 1 signal because two peaks exist that are spaced 200 ns apart.Above in FIG. 22, if Δ is 200 ns, then the autocorrelation of FIG. 22 ofthe multipath signal may erroneously be interpreted as a cyclic shift of−200 ns and a CSD mode 1.

FIGS. 27 to 34 define a first method to determine a CSD mode bysignaling CSD information between an access point and a mobile device,in accordance with some embodiments of the present invention. In thefirst method, a CSD mode is communicated by signaling from the networkside to the mobile device.

The CSD mode may be represented by: (1) a CSD mode from the IEEE 802.11nspecification; (2) a number of transmitters; (3) a cyclic shift(temporal) spacing between transmitters; (4) criteria forenabling/disabling a CSD mode; or (5) any combination of two or more ofthese representations (e.g., a number of transmitters plus a spacingbetween transmitters).

In FIG. 27, a server signals the current CSD mode from the server to themobile device. FIG. 28 shows a signaling message containing a number oftransmitters used for cyclic shift operations. FIG. 29 shows a signalingmessage containing a cyclic shift (temporal) spacing betweentransmitters (e.g., 50, 100 or 200 ns). FIG. 30 shows a signalingmessage containing criteria for enabling/disabling a CSD mode.

In FIG. 31, AP 100 sends a signaling message containing assistance dataidentifying the current CSD mode to MS 200. MS 200 uses the assistancedata to properly demodulate the CSD mode transmission. In FIG. 32, aserver 300′ sends the assistance data, including which CDS mode inoperational for each AP, to MS 200. Again, MS 200 uses the assistancedata to properly demodulate the CSD mode transmission.

FIG. 33 shows a combination of two or more of the above representations.AP 100 sends a signaling message containing assistance data to MS 200.The assistance data include: (1) the current CSD mode; (2) a number oftransmitters; (3) the temporal cyclic shift delay spacing betweentransmitters; and/or (4) criteria for enabling or disabling a CSD mode.As before, MS 200 uses the assistance data to properly demodulate theCSD mode transmission.

FIG. 34 shows crowd sourcing. In crowd sourcing, one or more mobiledevices determine what CSD mode is being used and report thisinformation to the server. The mobile device may also relay otherinformation about the current signaling conditions so the server may tryto determine what criteria is being used to enable and disable CSD. Afirst mobile (MS 200-1) or a plurality of mobiles each send to a server300′ a mobile report including a detected CSD mode, detected CSDparameters, parameters that an access point might use for a trigger(e.g., RSSI value, packer error rate (PER), data rate (DR), or the like)and/or a channel impulse response (CIR). The server 300′ uses thisreported information as crowd sourcing to determine a current CSD modeand/or trigger. Next, the server 300′ sends assistance data, includingthis current CSD mode and/or the trigger, to a second mobile (MS 200-2).

The signaling may be a unique and separate message or may be part of anexisting message, such as part of an assistance data message. Thissignaling may originate in an access point, or alternatively, thissignaling may originate from a server. A server may be instructed whatCSD mode is currently being used, for example, by a network operator.Alternatively, crowd sourcing may be used to determine what CSD mode iscurrently being used.

FIGS. 35 to 54 show how to determine a CSD mode by using a combinationof delay-based autocorrelation and cyclic shift-based autocorrelation,in accordance with some embodiments of the present invention.

FIG. 35 shows a CSD mode determination by comparing a difference betweentwo autocorrelations to a threshold. A first autocorrelation that is adelay-based autocorrelation 602 and a second autocorrelation that is acyclic shift-based autocorrelation 604. A received OFDM signal y(t) isused as an input to both correlators. A summer 606 takes a differencebetween the autocorrelation outputs and provides the difference as acorrelation output to a threshold comparison circuit 608. Thecorrelation output is compared to a threshold to derive a current CSDmode.

FIG. 36 defines a delay-based autocorrelation. The delay-basedautocorrelation attempts to determine if a multipath has adverselyaffected the received OFDM signal. In some embodiments, a delay-basedautocorrelation R(τ) is defined as:

${{R_{delay}^{k}(\tau)} = {\sum\limits_{i = {N_{g} + N_{S} - N_{C} + 1}}^{N_{g} + N_{S}}\;{{y(i)}{y^{*}\left( {i + \tau} \right)}}}},{or}$${R_{delay}^{k}(\tau)} = {{\sum\limits_{i = {N_{g} + N_{S} - N_{C} + 1}}^{N_{g} + N_{S} - \tau}\;{{y_{k}(i)}{y_{k}^{*}\left( {i + \tau} \right)}}} + {\sum\limits_{i = {N_{g} + N_{S} - \tau + 1}}^{N_{g} + N_{S}}\;{{y_{k}(i)}{{y_{k + 1}^{*}\left( {i + \tau - N_{g} - N_{S}} \right)}.}}}}$

As can be seen, a delay-based correlation does not take any cyclicshifting into consideration.

FIG. 37 defines a cyclic shift-based autocorrelation. The cyclicshift-based autocorrelation attempts to determine if an enabled CSD modehas affected the received OFDM signal. In some embodiments, a cyclicshift-based autocorrelation R(τ) is defined as:

${R_{CS}^{k}(\tau)} = {{\sum\limits_{i = {N_{g} + N_{S} - N_{C} + 1}}^{N_{g} + N_{S} - \tau}\;{{y_{k}(i)}{y_{k}^{*}\left( {i + \tau} \right)}}} + {\sum\limits_{i = {N_{g} + N_{S} - \tau + 1}}^{N_{g} + N_{S}}\;{{y_{k}(i)}{{y_{k}^{*}\left( {i + \tau - N_{S}} \right)}.}}}}$

FIGS. 38 and 39 show a range (N_(C)) for use in each autocorrelation ona multipath signal and a cyclic shift signal, respectively. In FIG. 38,a received signal experiences multipath, such thaty(t)=x(t)+x(t+Δ_(MP)). The multipath signal is delayed by Δ_(MP). Theend of the indirect path signal x(t+Δ_(MP)) is delayed such that theguard interval of the next symbol on the direct path signal interferes.The range of the autocorrelation excludes this overlapping region.Specifically, the beginning of the direct path signal x(t) is receivedat time zero. The beginning of the indirect path signal x(t+Δ_(MP)) isreceived at time Δ_(MP). In a worse case, the multipath delay Δ_(MP) is200 ns. The end of the guard interval of the direct path signal isreceived at N_(g). The end of a symbol of the direct path occurs atN_(S)+N_(g), where N_(S) is the symbol length and N_(g) is the guardinterval length. The range N_(C) is set to end at N_(S)+N_(g). Thebeginning is at N_(S)+N_(g)−N_(C). The width of N_(C) is variable.

In FIG. 39, a received signal y(t) is the sum of two direct path cyclicshifted signals. That is, y(t)=x(t)+x_(CS)(t), with the beginning of asymbol for each signal occurring at zero. The non-shifted signal isrepresented by x(t) and the cyclic shifted signal is represented byx_(CS)(t). In this case, the cyclic shift is Δ_(CS)=200 ns.

A worst case for multipath is multipath that cause two differentreceived signals to be delayed by 200 ns, three different receivedsignals to be delayed by 100 ns, or three different received signals tobe delayed by 50 ns each. These versions of multipath appear as comingfrom a cyclic shift delay system and are considered below.

A multipath signal y(t) is considered. FIG. 40 shows the output of adelay-based autocorrelator R(τ) when a multipath signal y(t) isreceived. In this example, the multipath signal y(t) arrives along twodifferent paths (e.g., a direct path and an indirect path). Theresulting delay-based autocorrelation of a multipath signal shows twopeaks. FIG. 41 shows the output of a cyclic shift-based autocorrelatorwhen the same multipath signal y(t) is received. The resulting cyclicshift-based autocorrelation of a multipath signal also shows two peaksindistinguishable from the delay-based autocorrelator output. FIG. 42shows a difference between the two autocorrelators for a multipathsignal y(t). The difference has no peak above a threshold.

A cyclic-shift signal y(t) is considered. FIG. 43 shows the output of adelay-based autocorrelator when a cyclic-shift signal y(t) is received.In this example, two transmitters are transmitting similar signals (onethe cyclic shift of the other) using a CSD mode (e.g., CSD mode 2). Theresulting output shows a single correlation peak. FIG. 44 shows theoutput of a cyclic shift-based autocorrelator when the same cyclic-shiftsignal y(t) is received. The resulting output shows two correlationpeaks. FIG. 45 shows a difference between the two autocorrelators forthe cyclic-shift signal y(t). The difference has one peak above athreshold.

Therefore, by comparing the outputs of a delay-based autocorrelator anda cyclic shift-based autocorrelator, one may differentiate between amultipath signal and a cyclic shift signal. That is, when theautocorrelators differ above a threshold, a cyclic shift signal isreceived.

In sum, for purely multipath signals, the output of the delay-basedautocorrelator is similar to the output of the cyclic shift-basedautocorrelator. For purely cyclic-shift signals, however, the output ofthe delay-based autocorrelator significantly differs from the output ofthe cyclic shift-based autocorrelator. Once the difference is detected,the number of transmitters may be identified from the number of peaks(e.g., 2, 3 or 4) above a threshold in the output results from thecyclic-shift autocorrelator. The temporal difference between successivepeaks identifies the cyclic-shift delay between signals (e.g., 50 ns,100 ns or 200 ns).

The same analysis applied above to a two-path multipath signal and a CSDmode 2 signal is now applied to a three-path multipath signal and a CSDmode 3 signal.

FIGS. 46 to 51 show the same graphs as shown in FIGS. 40 to 45, however,the received signal has either an additional multipath from a thirdsignal path or an additional CSD transmitted signal from a thirdtransmitter.

A multipath signal y(t) having a direct path and two indirect paths isconsidered. FIG. 46 shows the output of a delay-based autocorrelatorR(τ) when a multipath signal y(t) is received. In this example, themultipath signal y(t) arrives along three different paths (e.g., adirect path and two indirect paths). The resulting delay-basedautocorrelation of the multipath signal shows three peaks. FIG. 47 showsthe output of a cyclic shift-based autocorrelator when the samemultipath signal y(t) is received. The resulting cyclic shift-basedautocorrelation of a multipath signal also shows three peaksindistinguishable from the delay-based autocorrelator output. FIG. 48shows a difference between the two autocorrelators for a multipathsignal y(t). The difference has no peak above a threshold.

A cyclic-shift signal y(t) is considered. FIG. 49 shows the output of adelay-based autocorrelator when a cyclic-shift signal y(t) using CSDmode 3 is received. In this example, three transmitters are transmittingsimilar signals (two signals a cyclic shift of the first signal) usingCSD mode 3. The resulting output shows two correlation peaks. FIG. 50shows the output of a cyclic shift-based autocorrelator when the samecyclic-shift signal y(t) is received. The resulting output shows threecorrelation peaks. FIG. 51 shows a difference between the twoautocorrelators for the cyclic-shift signal y(t). The difference has twopeaks above a threshold.

FIG. 52 shows a method 500 to determine a current CSD mode from areceived OFDM signal y(t). At 502, a processor receives an OFDM signaly(t). At 504, the processor computes a delay-based autocorrelationR_(delay) ^(k)(τ) for N_(C) samples. At 506, the processor computes acyclic shift-based autocorrelation R_(CS) ^(k)(τ) for N_(C) samples.Steps 504 and 506 may be performed in either order or in parallel. At508, the processor computes a difference R_(CS) ^(k)(τ)−R_(delay)^(k)(τ). At 510, the processor compares the difference to a threshold.At 512, the processor determines if CSD is enable and what CSD mode isenables. At 514, the processor determines a proper RTT signal used forposition estimates. The proper signal to use for RTT is the last-in-timesignal or the signal transmitted from the first transmitter without acyclic shift.

FIGS. 53 and 54 show how to take an average correlation over time toprovide a normalized autocorrelation.

In FIG. 53, a method 600 to normalize a delay-based autocorrelation isshown. At 602, a processor computes a delay-based autocorrelationR_(delay) ^(k)(τ), for each of K OFDM symbols, across the last N_(C)samples. Alternatively, the first N_(C) samples may be examined. Next at604, the processor computes an average delay-based autocorrelationacross the K OFDM symbols, for example, as

${R_{delay}(\tau)} = {\frac{1}{K}{\sum\limits_{k = 1}^{K}\;{{R_{delay}^{k}(\tau)}.}}}$Finally at 606, the processor computes a normalized delay-basedautocorrelation, for example, as

${R_{delay}^{norm}(\tau)} = {\frac{{R_{delay}(\tau)}}{{R_{delay}(0)}}.}$

In FIG. 54, a method 610 to normalize a cyclic shift-basedautocorrelation is shown. At 612, a processor computes a cyclicshift-based autocorrelation R_(CS) ^(k)(τ), for each of K OFDM symbols,across the last N_(C) samples. Alternatively, the first N_(C) samplesmay be examined. Next at 614, the processor computes an average cyclicshift-based autocorrelation across the K OFDM symbols, for example, as

${R_{CS}(\tau)} = {\frac{1}{K}{\sum\limits_{k = 1}^{K}\;{{R_{CS}^{k}(\tau)}.}}}$Finally at 616, the processor computes a normalized delay-basedautocorrelation, for example, as

${R_{CS}^{norm}(\tau)} = {\frac{{R_{CS}(\tau)}}{{R_{CS}(0)}}.}$

FIGS. 55 to 60 illustrate another method to determine a CSD mode byusing a channel impulse response calculation, in accordance with someembodiments of the present invention. A CSD mode is determined byexamining local maxima above a threshold in a channel impulse responseof a received OFDM signal.

The number of local maxima or peaks above a threshold in a channelimpulse response determines the number of CSD transmitters. The temporalspacing of the CSD transmitters is determined by finding the timedifference between these peaks. By tabulating the number of local peaksand their time spacing over time after several OFDM symbol periods, onemay determine what CSD mode is currently being used.

FIG. 55 shows an example of a channel impulse response (CIR) of an OFDMsignal from a two-transmitter system transmitting CSD signals with acyclic shift of δt. A threshold value too high will miss peaks in actual(non-theoretical) channel impulse response data. A threshold value toolow will count extra peaks in actual channel impulse response data.Channel impulse response of several symbols (K OFDM symbols) over timewith a threshold value in between will result in a compromise where mostof the time the correct number of peaks are found.

FIG. 56 shows an example of a channel impulse response of an OFDM signalfrom a three-transmitter system transmitting CSD signals with a cyclicshift of δt between successive pairs of peaks. FIG. 57 shows actual dataof a channel impulse response when only a single transmitter is used.FIG. 58 shows actual data of a channel impulse response when only threetransmitters are used. The plotted data shows two strong peaks and aweak peak in the measured OFDM signal. For a single window, one of thepeaks might be missed for a single OFDM symbol time. Over severalwindows, however, the correct number of peaks will be found. In atypical case, the correct number of peaks found will outnumbering thenumber of times a peak is missed.

FIG. 59 shows a method 700 to determine, over the time of K OFDMsymbols, a number of CSD transmitters. At 702, a loop beings for each KOFDM symbols to receive and process measurements. For each symbol, theloop is shown in more detail. At 704, a receiver receives measurementsof the OFDM symbol. At 706, a processor computes a channel impulseresponse (CIR) based on the received samples. At 708, the processordetermines a number of local maximums above a certain threshold. At 710,the processor increments a counter representing a number of localmaximums found over time. The loop repeats with a new OFDM symbol. At712, once the loop completes, the processor selects a counter with thelargest number to determine a number of transmitters used.

FIG. 60 shows a method 800 to determine, over the time of K OFDMsymbols, a number of CSD transmitters and a temporal cyclic shift amongthose CSD transmitters. At 802, a loop beings for each K OFDM symbols toreceive and process measurements. For each symbol, the loop is shown inmore detail. At 804, a receiver receives measurements of the OFDMsymbol. At 806, a processor computes a channel impulse response (CIR)based on the received samples. At 808, the processor determines a numberof local maximums above a threshold. At 810, the processor determines atime difference (δt) between each adjacent pair of local maximums thatare above a threshold. At 812, the processor records a time differencefrom one plot (δt₁, δt₂ or δt₃) as a set that is indexed by a number oflocal maximums above the threshold. The loop repeats with a new OFDMsymbol. At 814, once the loop completes, the processor selects a numberof maximums with the most sets and then determines an average of thosetime differences to determine a current CSD mode. Optionally, theprocessor also determines if a standard deviation of δt is below athreshold.

The methodologies described herein may be implemented by various meansdepending upon the application. For example, these methodologies may beimplemented in hardware, firmware, software, or any combination thereof.For a hardware implementation, the processing units may be implementedwithin one or more application specific integrated circuits (ASICs),digital signal processors (DSPs), digital signal processing devices(DSPDs), programmable logic devices (PLDs), field programmable gatearrays (FPGAs), processors, controllers, micro-controllers,microprocessors, electronic devices, other electronic units designed toperform the functions described herein, or a combination thereof.

For a firmware and/or software implementation, the methodologies may beimplemented with modules (e.g., procedures, functions, and so on) thatperform the functions described herein. Any machine-readable mediumtangibly embodying instructions may be used in implementing themethodologies described herein. For example, software codes may bestored in a memory and executed by a processor unit. Memory may beimplemented within the processor unit or external to the processor unit.As used herein the term “memory” refers to any type of long term, shortterm, volatile, nonvolatile, or other memory and is not to be limited toany particular type of memory or number of memories, or type of mediaupon which memory is stored.

If implemented in firmware and/or software, the functions may be storedas one or more instructions or code on a computer-readable medium.Examples include computer-readable media encoded with a data structureand computer-readable media encoded with a computer program.Computer-readable media includes physical computer storage media. Astorage medium may be any available medium that can be accessed by acomputer. By way of example, and not limitation, such computer-readablemedia can comprise RAM, ROM, EEPROM, CD-ROM or other optical diskstorage, magnetic disk storage or other magnetic storage devices, or anyother medium that can be used to store desired program code in the formof instructions or data structures and that can be accessed by acomputer; disk and disc, as used herein, includes compact disc (CD),laser disc, optical disc, digital versatile disc (DVD), floppy disk andBlu-ray disc where disks usually reproduce data magnetically, whilediscs reproduce data optically with lasers. Combinations of the aboveshould also be included within the scope of computer-readable media.

In addition to storage on computer readable medium, instructions and/ordata may be provided as signals on transmission media included in acommunication apparatus. For example, a communication apparatus mayinclude a transceiver having signals indicative of instructions anddata. The instructions and data are configured to cause one or moreprocessors to implement the functions outlined in the claims. That is,the communication apparatus includes transmission media with signalsindicative of information to perform disclosed functions. At a firsttime, the transmission media included in the communication apparatus mayinclude a first portion of the information to perform the disclosedfunctions, while at a second time the transmission media included in thecommunication apparatus may include a second portion of the informationto perform the disclosed functions.

The previous description of the disclosed aspects is provided to enableany person skilled in the art to make or use the present disclosure.Various modifications to these aspects will be readily apparent to thoseskilled in the art, and the generic principles defined herein may beapplied to other aspects without departing from the spirit or scope ofthe disclosure.

What is claimed is:
 1. A method for finding cyclic shift diversity (CSD)using autocorrelations, the method comprising: receiving, with areceiver, an orthogonal frequency-division multiplexing (OFDM) signal;computing, with at least one processor, a delay-based autocorrelation ofthe OFDM signal to form a delay-based autocorrelation result; computing,with the at least one processor, a cyclic shift-based autocorrelation ofthe OFDM signal to form a cyclic shift-based autocorrelation result;comparing, with the at least one processor, the delay-basedautocorrelation result to the cyclic shift-based autocorrelation resultto form a comparison; and determining, with the at least one processor,a CSD mode based on the comparison.
 2. The method of claim 1, whereinthe delay-based autocorrelation and the cyclic shift-basedautocorrelation comprise autocorrelations of N_(C) samples.
 3. Themethod of claim 1, wherein the delay-based autocorrelation comprisesR_(delay) ^(k)(τ) defined as:${R_{delay}^{k}(\tau)} = {{\sum\limits_{i = {N_{g} + N_{S} - N_{C} + 1}}^{N_{g} + N_{S} - \tau}\;{{y_{k}(i)}{y_{k}^{*}\left( {i + \tau} \right)}}} + {\sum\limits_{i = {N_{g} + N_{S} - \tau + 1}}^{N_{g} + N_{S}}\;{{y_{k}(i)}{y_{k + 1}^{*}\left( {i + \tau - N_{g} - N_{S}} \right)}}}}$where N_(g) is a number of samples of a guard band; where N_(S) is anumber of samples of one OFDM symbol; where N_(C) is a number of samplesof the delay-based autocorrelation; and where k is an index of OFDMsymbols.
 4. The method of claim 1, wherein the cyclic shift-basedautocorrelation comprises R_(CS) ^(k)(τ) defined as:${R_{CS}^{k}(\tau)} = {{\sum\limits_{i = {N_{g} + N_{S} - N_{C} + 1}}^{N_{g} + N_{S} - \tau}\;{{y_{k}(i)}{y_{k}^{*}\left( {i + \tau} \right)}}} + {\sum\limits_{i = {N_{g} + N_{S} - \tau + 1}}^{N_{g} + N_{S}}\;{{y_{k}(i)}{y_{k}^{*}\left( {i + \tau - N_{S}} \right)}}}}$where N_(g) is a number of samples of a guard band; where N_(S) is anumber of samples of one OFDM symbol; where N_(C) is a number of samplesof the cyclic shift-based autocorrelation; where k is a number of OFDMsymbols; and where y_(k)( ) represents input samples of a k^(th) OFDMsymbol in the OFDM signal.
 5. The method of claim 1, wherein thedelay-based autocorrelation and the cyclic shift-based autocorrelationboth comprise an autocorrelation of N_(C) samples taken from a leadingedge of the OFDM signal.
 6. The method of claim 1, wherein thedelay-based autocorrelation and the cyclic shift-based autocorrelationcomprise an autocorrelation of N_(C) samples taken from a trailing edgeof the OFDM signal.
 7. The method of claim 1, wherein comparing thedelay-based autocorrelation result to the cyclic shift-basedautocorrelation result to form the comparison comprises: computing adifference between the delay-based autocorrelation result to the cyclicshift-based autocorrelation result; and comparing the difference to athreshold.
 8. The method of claim 1, wherein determining the CSD modebased on the comparison comprises determining a number of transmittersin the OFDM signal.
 9. The method of claim 1, wherein determining theCSD mode based on the comparison comprises determining a temporaldifference in the OFDM signal.
 10. The method of claim 1, whereindetermining the CSD mode based on the comparison comprises: determininga number of transmitters in the OFDM signal; and determining a temporaldifference in the OFDM signal.
 11. The method of claim 1, furthercomprising selecting a round-trip time (RTT) signal based on the CSDmode.
 12. The method of claim 11, further comprising estimating aposition based on the selected RTT signal.
 13. The method of claim 1,wherein: receiving the OFDM signal comprises receiving k OFDM symbols;computing the delay-based autocorrelation of the OFDM signal to form thedelay-based autocorrelation result comprises: computing a delay-basedaverage of k delay-based autocorrelation of the k OFDM symbols; andnormalizing the delay-based average to form the delay-basedautocorrelation result; and computing the cyclic shift-basedautocorrelation of the OFDM signal to form the cyclic shift-basedautocorrelation result comprises: computing a cyclic shift-based averageof k cyclic shift-based autocorrelation of the k OFDM symbols; andnormalizing the cyclic shift-based average to form the cyclicshift-based autocorrelation result.
 14. A mobile device for findingcyclic shift diversity (CSD) using autocorrelations, the mobile devicecomprising: a transceiver, the transceiver for receiving an orthogonalfrequency-division multiplexing (OFDM) signal; and a processor coupledto the transceiver, the processor for: computing a delay-basedautocorrelation of the OFDM signal to form a delay-based autocorrelationresult; computing a cyclic shift-based autocorrelation of the OFDMsignal to form a cyclic shift-based autocorrelation result; comparingthe delay-based autocorrelation result to the cyclic shift-basedautocorrelation result to form a comparison; and determining a CSD modebased on the comparison.
 15. The mobile device of claim 14, wherein thedelay-based autocorrelation and the cyclic shift-based autocorrelationboth comprise an autocorrelation of N_(C) samples taken from a leadingedge of the OFDM signal.
 16. The mobile device of claim 14, wherein thedelay-based autocorrelation and the cyclic shift-based autocorrelationcomprise an autocorrelation of N_(C) samples taken from a trailing edgeof the OFDM signal.
 17. The mobile device of claim 14, wherein theprocessor for determining the CSD mode based on the comparison comprisesa processor for determining a number of transmitters in the OFDM signal.18. The mobile device of claim 14, wherein the processor is further forselecting a round-trip time (RTT) signal based on the CSD mode.
 19. Themobile device of claim 18, wherein the processor is further forestimating a position based on the selected RTT signal.
 20. A mobiledevice for finding cyclic shift diversity (CSD) using autocorrelations,the mobile device comprising: means for receiving an orthogonalfrequency-division multiplexing (OFDM) signal; means for computing adelay-based autocorrelation of the OFDM signal to form a delay-basedautocorrelation result; means for computing a cyclic shift-basedautocorrelation of the OFDM signal to form a cyclic shift-basedautocorrelation result; means for comparing the delay-basedautocorrelation result to the cyclic shift-based autocorrelation resultto form a comparison; and means for determining a CSD mode based on thecomparison.
 21. The mobile device of claim 20, wherein the delay-basedautocorrelation and the cyclic shift-based autocorrelation both comprisean autocorrelation of N_(C) samples taken from a leading edge of theOFDM signal.
 22. The mobile device of claim 20, wherein the delay-basedautocorrelation and the cyclic shift-based autocorrelation comprise anautocorrelation of N_(C) samples taken from a trailing edge of the OFDMsignal.
 23. The mobile device of claim 20, wherein the processor isfurther for selecting a round-trip time (RTT) signal based on the CSDmode.
 24. A non-volatile computer-readable storage medium includingprogram code stored thereon, comprising program code for: receiving anorthogonal frequency-division multiplexing (OFDM) signal; computing adelay-based autocorrelation of the OFDM signal to form a delay-basedautocorrelation result; computing a cyclic shift-based autocorrelationof the OFDM signal to form a cyclic shift-based autocorrelation result;comparing the delay-based autocorrelation result to the cyclicshift-based autocorrelation result to form a comparison; and determininga CSD mode based on the comparison.
 25. The non-volatilecomputer-readable storage medium of claim 24, wherein the delay-basedautocorrelation and the cyclic shift-based autocorrelation both comprisean autocorrelation of N_(C) samples taken from a leading edge of theOFDM signal.
 26. The non-volatile computer-readable storage medium ofclaim 24, wherein the delay-based autocorrelation and the cyclicshift-based autocorrelation comprise an autocorrelation of N_(C) samplestaken from a trailing edge of the OFDM signal.
 27. The non-volatilecomputer-readable storage medium of claim 24, wherein the program codecomprises is further for selecting a round-trip time (RTT) signal basedon the CSD mode.